Structure Determination Research Articles

Protein complex structure modeling by cross-modal alignment between cryo-EM maps and protein sequences

Cryo-electron microscopy (cryo-EM) technique is widely used for protein structure determination. Current automatic cryo-EM protein complex modeling methods mostly rely on prior chain separation. However, chain separation without sequence guidance often suffers from errors caused by cross-chain interaction or noise densities, which would accumulate and mislead the subsequent steps. Here, we present EModelX, a fully automated cryo-EM protein complex structure modeling method, which achieves sequence-guiding modeling through cross-modal alignments between cryo-EM maps and protein sequences. EModelX first employs multi-task deep learning to predict Cα atoms, backbone atoms, and amino acid types from cryo-EM maps, which is subsequently used to sample Cα traces with amino acid profiles. The profiles are then aligned with protein sequences to obtain initial structural models, which yielded an average RMSD of 1.17 Å in our test set, approaching atomic-level precision in recovering PDB-deposited structures. After filling unmodeled gaps through sequence-guiding Cα threading, the final models achieved an average TM-score of 0.808, outperforming the state-of-the-art method. The further combination with AlphaFold can improve the average TM-score to 0.911. Analyzes conducted by comparing some EModelX-built models and PDB structures highlight its potential to improve PDB structures. EModelX is accessible at https://bio-web1.nscc-gz.cn/app/EModelX.

Atomically precise Cu32 nanoclusters with selenide doping: Synthesis, bonding, and catalysis

AbstractCopper nanoclusters with stable compositions and precise structures have long been sought after, as they possess properties that are absent in gold and silver counterparts. However, the creation of copper nanoclusters with novel compositions, structures, and functionalities remains largely unexplored in the literature. In this study, we demonstrate that selenide doping is an effective method for fabricating stable copper nanostructures through controlled synthesis and structure determination of a copper–selenide nanocluster. The nanocluster of [Cu32Se7(BnSe)18(PPh3)6]+ (denoted as Cu32Se7, Bn is benzyl) has been prepared by reducing copper salts in the presence of organic diselenides. The atomic structure of the Cu32Se7 cluster, accurately determined through single‐crystal X‐ray diffraction, reveals a core–shell arrangement of Cu20Se7@Cu12(BnSe)18(PPh3)6, where Se2− anions are well dispersed in the Cu20 framework. Notably, this cluster represents a rare example of copper–selenide semiconductor nanoclusters. Experimental and theoretical analysis shows strong interactions between Se ligands and metal atoms, resulting in high stability of the Cu32Se7 cluster. Furthermore, the cluster exhibits excellent catalytic performance in the hydroboration reaction of alkynes, producing a range of vinylboron compounds with adjustable structures and functions. Importantly, the cluster undergoes no structural or nuclearity changes during the reaction, as confirmed by extended X‐ray absorption fine structure and X‐ray photoelectron spectroscopy studies. This study not only presents a molecular cluster model highlighting the effectiveness of selenide dopants in fabricating new copper nanostructures but also paves the way for utilizing stable copper nanoclusters in diverse and exciting areas beyond catalysis.

Approximate and Exact Optimization Algorithms for the Beltway and Turnpike Problems with Duplicated, Missing, Partially Labeled, and Uncertain Measurements.

The Turnpike problem aims to reconstruct a set of one-dimensional points from their unordered pairwise distances. Turnpike arises in biological applications such as molecular structure determination, genomic sequencing, tandem mass spectrometry, and molecular error-correcting codes. Under noisy observation of the distances, the Turnpike problem is NP-hard and can take exponential time and space to solve when using traditional algorithms. To address this, we reframe the noisy Turnpike problem through the lens of optimization, seeking to simultaneously find the unknown point set and a permutation that maximizes similarity to the input distances. Our core contribution is a suite of algorithms that robustly solve this new objective. This includes a bilevel optimization framework that can efficiently solve Turnpike instances with up to 100,000 points. We show that this framework can be extended to scenarios with domain-specific constraints that include duplicated, missing, and partially labeled distances. Using these, we also extend our algorithms to work for points distributed on a circle (the Beltway problem). For small-scale applications that require global optimality, we formulate an integer linear program (ILP) that (i) accepts an objective from a generic family of convex functions and (ii) uses an extended formulation to reduce the number of binary variables. On synthetic and real partial digest data, our bilevel algorithms achieved state-of-the-art scalability across challenging scenarios with performance that matches or exceeds competing baselines. On small-scale instances, our ILP efficiently recovered ground-truth assignments and produced reconstructions that match or exceed our alternating algorithms. Our implementations are available at https://github.com/Kingsford-Group/turnpikesolvermm.

CryoSeek: A strategy for bioentity discovery using cryoelectron microscopy

Structural biology is experiencing a paradigm shift from targeted structural determination to structure-guided discovery of previously uncharacterized bioentities. We employed cryoelectron microscopy (cryo-EM) to analyze filtered water samples collected from the Tsinghua Lotus Pond. Here, we report the structural determination and characterization of two highly similar helical fibrils, named TLP-1a and TLP-1b, each approximately 8 nm in diameter with a 15-Å wide tunnel. These fibrils are assembled from a similar protein protomer, whose structure was conveniently automodeled in CryoNet. The protomer structure does not match any available experimental structures, but shares the same fold as many predicted structures of unknown functions. The amino-terminal β strand of protomer n + 4 inserts into a cleft in protomer n to complete an immunoglobulin (Ig)-like domain. This packing mechanism, known as donor-strand exchange (DSE), has been observed in several bacterial pilus assemblies, wherein the donor is protomer n + 1. Despite distinct shape and thickness, this reminiscence suggests that TLP-1a/b fibrils may represent uncharacterized bacterial pili. Our study demonstrates an emerging paradigm in structural biology, where high-resolution structural determination precedes and drives the identification and characterization of completely unknown objects.

Structural insights into inhibitor mechanisms on immature HIV-1 Gag lattice revealed by high-resolution in situ single-particle cryo-EM.

HIV-1 inhibitors, such as Bevirimat (BVM) and Lenacapavir (LEN), block the production and maturation of infectious virions. However, their mechanisms remain unclear due to the absence of high-resolution structures for BVM complexes and LEN's structural data being limited to the mature capsid. Utilizing perforated virus-like particles (VLPs) produced from mammalian cells, we developed an approach to determine in situ cryo-electron microscopy (cryo-EM) structures of HIV-1 with inhibitors. This allowed for the first structural determination of the native immature HIV-1 particle with BVM and LEN bound inside the VLPs at high resolutions. Our findings offer a more accurate model of BVM engaging the Gag lattice and, importantly, demonstrate that LEN not only binds the mature capsid but also targets the immature lattice in a distinct manner. The binding of LEN induces a conformational change in the capsid protein (CA) region and alters the architecture of the Gag lattice, which may affect the maturation process. These insights expand our understanding of the inhibitory mechanisms of BVM and LEN on HIV-1 and provide valuable clues for the design of future inhibitors.

Unveiling short-range magnetic correlations: The development of magnetic pair distribution function method at CSNS

Recent advancements in the magnetic pair distribution function (mPDF) analysis of neutron total scattering data provide a powerful approach to investigate local magnetic correlations in materials. This technique is promising for revealing short-range magnetic correlations at the sub-nanometer length scale directly in real space. It is particularly suitable for strongly correlated electron systems and geometrically frustrated magnets. In this study, the mPDF experiment is conducted at the multi-physics instrument (MPI) of the China Spallation Neutron Source, one of the latest neutron total scattering diffractometers in the world. We systematically benchmarked a series of important parameters related to the experimental setup and data processing for mPDF experiments at the MPI and similar instruments. This method not only advances the magnetic structure determination of fundamental materials but also opens the door for extending mPDF studies to more complicated and frontier magnetic systems that are challenging for conventional diffraction methods.

Structural Study on Alkali‐Carboxylate Functionalized Late‐Transition Metal Bis(dithiocarbamate) Complexes

AbstractLithium, sodium, and potassium derivatives of amino‐acid derived bis(dithiocarbamate) complexes of bivalent nickel, palladium, platinum, and copper are readily available by treatment of the carboxylic‐acid functionalized complexes with the respective alkali metal hydroxide. Representative derivatives of the types A4[M(L1)2], A2[M(HL1)2], A[M(HL1)(H2L1)] (N‐dithioato‐iminodiacetate, L1), and A2[M(L2,3)2] (N‐dithioato‐l‐prolinate, L2, and ‐N‐benzylglycinate, L3; A=Li, Na, K; M=Ni, Pd, Pt, Cu) were isolated and characterized by spectroscopic and thermal methods. Six entries were accessible to single‐crystal X‐ray structure determination, revealing the presence of different coordination‐polymeric structures and hydrogen‐bonded assemblies comprising solvent‐separated cations in the solid state. While the transition metal always retains its all‐sulfur coordination with defined geometry, the alkali metals are structurally more flexible. The latter are usually coordinated by carboxylate and water, but additional interactions with sulfur donors are also relevant in some cases.

Superlattice Assembly for Empowering Metal Nanoclusters.

ConspectusAtomically precise metal nanoclusters, serving as an aggregation state of metal atoms, display unique physicochemical properties owing to their ultrasmall sizes with discrete electronic energy levels and strong quantum size effects. Such intriguing properties endow nanoclusters with potential utilization as efficient nanomaterials in catalysis, electron transfer, drug delivery, photothermal conversion, optical control, etc. With the assistance of atomically precise operations and theoretical calculations on metal nanoclusters, significant progress has been accomplished in illustrating their structure-performance correlations at the single-molecule level. Such research achievements, in turn, have contributed to the rational design and customization of functional nanoclusters and cluster-based nanomaterials.Most previous studies have focused on investigating structure-property correlations of nanocluster monomers, while the exploration of electronic structures and physicochemical properties of hierarchical cluster-based assembled structures was far from enough. Indeed, from the application aspect, the nanoclusters with controllably assembly states (e.g., crystalline assembled materials, host-guest hybrid materials, amorphous powders, and so on) were more suitable for performance expression relative to those in the monomeric state and more directed to downstream solid-state applications. In this context, more attention should be paid to the state-correlated property variations of metal nanoclusters occurring in their aggregating and assembling processes for better applications in accordance with their aptitude.Crystalline aggregates are crucial in the structural determination of metal nanoclusters, also acting as a cornerstone to analyze the structure-property correlations by affording atomic-level information. The regular arrangement, uniform composition, and close intermolecular distance of the cluster molecules in their supercrystal lattices are beneficial for property retention and amplification from the molecule itself as a monomeric state. Besides, for these nanoparticles with strong quantum size effects, the intercluster distances in the supercrystal lattices are still located at the nanoscale level, wherein the quantum size effect is highly likely to take effect with additional intermolecular synergistic effects. Accordingly, it is expected that novel performances might occur in the crystalline aggregates of nanoclusters that are completely different from those in the monomolecular state.In this Account, we emphasize our efforts in exploring the performance enhancement of atomically precise metal nanoclusters in their crystalline aggregate states, such as thermal stability, photoluminescence, optical activity, and an optical waveguide. Such performance enhancements further supported the practical uses of metal nanoclusters in structure determination, a polarization switch, an optical waveguide device, and so on. We also demonstrated that the differences in physicochemical properties between crystalline aggregates and monomers of metal nanoclusters might be attributed to the change in electronic structures during the crystalline aggregation processes in the superlattice. The "superlattice assembly" is intended to customize the function of cluster-based aggregates for downstream solid-state applications.

Study of the Torquoselectivity of a Set of Unusual Ring‐Opening Electrocyclic Reactions: Determination of the Electronic Bonding Structure Through the Methodologies of Natural Bond Orbital Analysis and Quantum Theory of Atoms in Molecules, and Analysis of the Electronic Reaction Mechanism Through Bond Reactivity Descriptors

ABSTRACTIn this work, we have studied the torquoselectivity of a set of unusual ring‐opening electrocyclic reactions that have not been successfully rationalized using models based on orbital symmetry nor have they been explained by steric hindrance. Firstly, the corresponding transition states have been obtained, and it has been verified that the intrinsic reaction coordinates associated with these transition states are consistent with the reactants and products of the reactions studied. This has allowed us to theoretically calculate the reaction barriers (with their corresponding thermal corrections) and compare them with the corresponding experimental values. In a second step, we have analyzed the electronic bonding structure using the methodologies of Natural Bond Orbital Analysis and Quantum Theory of Atoms in Molecules, searching for interactions that may significantly stabilize the transition states. Finally, we have analyzed the reactivity using a recent model that has allowed us to calculate the corresponding bond reactivity descriptors.

The Impact of Employee Stock Ownership Plans on Capital Structure Decisions: Evidence from China

The determination of the capital structure is a critical component of a company’s financial decision-making process. The question of how to optimize a firm’s capital structure to increase its value has been a significant topic of interest within the financial community. The employee stock ownership plan (ESOP) has developed rapidly in China’s capital market over the past decade, providing a suitable context for studying the impact of employee equity incentives on capital structure decisions. This paper employs cross-sectional ordinary least squares regression models and unbalanced panel fixed effect models to investigate the impact of employee stock ownership plans (ESOPs) on firms’ capital structure decisions. The analysis is conducted on a sample of Chinese A-share listed companies on the Shanghai and Shenzhen Stock Exchanges. The research considers both static capital structure choice and dynamic capital structure adjustment. We find that the implementation of an ESOP reduces the level of corporate debt and accelerates the dynamic adjustment of capital structure, suggesting that employee equity incentives play a role in optimizing firms’ capital structure decisions. We also find that the impact of ESOPs on the dynamic adjustment of capital structure is asymmetric. Specifically, the implementation of ESOPs markedly accelerates the downward adjustment of capital structure, yet has no impact on the upward adjustment of capital structure. Further analysis demonstrates that the impact of ESOPs on capital structure decisions is contingent upon the macroeconomic environment, industry characteristics, corporate governance, and ESOP contract designs. First, the optimization of ESOPs on capital structure decisions is more pronounced in an economic boom environment, in a poor market climate, or in competitive industries. Second, the reduction effect of ESOPs on corporate debt is more pronounced in non-state-owned companies, high-tech companies and those with lower ownership concentration. In contrast, the acceleration effect of ESOPs on capital structure adjustment is more pronounced in state-owned companies, non-high-tech companies and those with higher ownership concentration. Ultimately, ESOPs financed by loans from a firm’s major shareholders—or with a longer lock-up period, smaller shareholding size or executive subscription ratio—demonstrate a more pronounced optimization effect on capital structure decisions. This paper not only contributes to the existing literature on the relationship between equity incentives and capital structure decisions, but also provides guidance for listed companies on the reasonable design of their ESOPs and the optimization of their capital structure decisions.

Study on the extraction of Phycocyanin and the impact of in vitro simulated digestion on its anti-diabetic ability

Phycocyanin (PC) has significant anti-diabetic activity. However, research on the impact of digestion on the anti-diabetic properties of PC is still rare. In this study, we successfully extracted food-grade PC with a purity of 1.64 ± 0.06 from Ge Xian Mi. The results of antioxidant and enzyme activity inhibition experiments indicate that the biological activity of PC is positively correlated with its purity. Fluorescence and UV–Vis spectroscopy revealed the degradation of apolipoprotein and chromophore structures in PC during digestion. During digestion, the characteristic peaks of chromophores gradually disappeared, accompanied by a continuous decrease in antioxidant activity. The results of secondary structure determination indicate that after 0.5 h of digestion, the α-helix content decreased by approximately 50%, while the β-sheet content decreased by 6.87%. At the end of digestion, the α-helix structure was completely lost. The inhibitory effect of PC on the two enzymes decreased by approximately 20% after digestion started, followed by a rebound at 1.0 h, and then declined again at 3.0 h. At the end of digestion, the inhibition rates against α-amylase and α-glucosidase were only 22.09% and 25.76%, respectively. Digestion significantly decreased the antidiabetic ability of PC.

Four decades of Eukaryotic DNA replication: From yeast genetics to high-resolution cryo-EM structures of the replisome

I had my eyes set on DNA replication research when I took my first molecular biology course in graduate school. My election to the National Academy of Sciences came just when I was retiring from active research. It gives me an opportunity to reflect on my personal journey in eukaryotic DNA replication research, which started as a thought experiment and culminated in witnessing the determination of the cryoelectron microscopic structure of the yeast replisome in the act of transferring histone-encoded epigenetic information at the replication fork. I would like to dedicate this inaugural article to my talented trainees and valuable collaborators in gratitude for the joy they gave me in this journey. I also want to thank my mentors who instilled in me the purpose of science. I hope junior scientists will not be disheartened by the marathon nature of research, but mindful enough to integrate and pause for other equally fun and meaningful activities of life into the marathon.

Structure determination of tweezer-shaped π-extended tetraphenylenes by microcrystal electron diffraction

Abstract The structure determination of large π-conjugated molecules using microcrystal electron diffraction (MicroED) was demonstrated. The poorly soluble solids of the tweezer-shaped molecules were subjected directly from the reaction vessel to MicroED to determine their structures and packing modes. This work validated the efficiency of MicroED in determining the structures of such compounds.

The role of structure in regulatory RNA elements.

Regulatory RNA elements fulfill functions such as translational regulation, control of transcript levels, and regulation of viral genome replication. Trans-acting factors (i.e. RNA-binding proteins) bind the so-called cis elements and confer functionality to the complex. The specificity during protein-RNA complex (RNP) formation often exploits the structural plasticity of RNA. Functional integrity of cis-trans pairs depends on the availability of properly folded RNA elements, and RNA conformational transitions can cause diseases. Knowledge of RNA structure and the conformational space is needed for understanding complex formation and deducing functional effects. However, structure determination of RNAs under in vivo conditions remains challenging. This review provides an overview of structured eukaryotic and viral RNA cis elements and discusses the effect of RNA structural equilibria on RNP formation. We showcase implications of RNA structural changes for diseases, outline strategies for RNA structure-based drug targeting, and summarize the methodological toolbox for deciphering RNA structures.

Alkylaluminum Complexes Featuring Bridged Bis-Formylfluorenimide Ligands for Hydroboration of Aldehyde, Ketone, and Imines.

Three bis-formylfluorenimide ligands with different bridging groups were designed and synthesized, leading to the successful preparation of six novel alkylaluminum complexes through their reaction with alkylaluminum reagents (AlMe3 or AlEt3). Complexes 1 and 2 were obtained by the reaction of 1,2-propylene-bridged diamine (L1) with AlMe3 or AlEt3. By reacting 1,2-cyclohexylene-bridged diamine (L2) with AlMe3 or AlEt3 to obtain complexes 3 and 4. The above ligands formed a bidentate four-coordinate structure with alkylaluminum, which involved the elimination of one alkyl group as the ligand reacted with alkylaluminum. The complexes 5 and 6 were synthesized through the reaction of 1,2-phenylene-bridged diamine (L3) with AlEt3 in toluene or tetrahydrofuran. Notably, L3 exhibited unique reactivity compared with the other ligands, which formed a tridentate four-coordinated structure when reacting with alkylaluminum. The formation of the tridentate complex resulted from the introduction of a benzimidazole derivative or tetrahydrofuran (THF) molecule along with the elimination of two alkyl groups during its coordination with alkylaluminum. All complexes were characterized via 1H NMR, 13C NMR, and elemental analysis, with structural determination confirmed through X-ray. Furthermore, the catalytic activity in the hydroboration reaction of aldehyde, ketone, and imines was investigated with these complexes as catalysts. Among them, complex 1 demonstrated excellent catalytic performance (up to 99% yield) and broad substrate compatibility (more than 30 substrates) at low catalyst loading (1 mol %) under mild reaction conditions.

Structural determination, energy transfer and color-tunable photoluminescence of stable LiYSiO4: Ce/Tb/Sm Phosphors toward nUV pumped wLEDs application

Study on photon emission of Ce3+-doped phosphors is essential for advanced optoelectronic application. However, it remains quite difficult to design near-ultraviolet excitable Ce3+-activated silicate blue/cyan-emitting phosphors because of the combined influence of iconicity of Ce3+, crystal field strength, and nephelauxetic effect. Herein, Ce3+ incorporated into a proper host LiYSiO4 (LYS) phosphor is mechanistically investigated and shown efficient blue/cyan photoluminescence (PL) owing to Ce3+ 5d1 electronic state experiencing appropriate crystal field splitting. The comprehensive analysis based on structural refinement, dynamic/static spectra, and density functional theory calculations indicates that Ce3+ ions are energetically favored in octahedral Y site as compared with Li site in the host, resulting in attractive PL properties. According to the principle of color superposition and via cascading energy transfer (ET) from Ce3+ → Tb3+ → Sm3+, systematic PL tuning in a large color gamut is realized by further codoping with the green- and red-emissions of Tb3+ and Sm3+ in the phosphor LYS: Ce3+/Tb3+/Sm3+. The direct ET from Ce3+ → Sm3+ is difficult to occur due to the metal-metal charge transfer effect. Of note, the PL thermal-quenching of Ce3+ is mainly associated with multiphonon relaxation, while the quenching of Tb3+/ Sm3+ is primarily due to the cross relaxation (CR) process via dipole-dipole (d-d) interaction. The appropriate distance between the two nearest adjacent Y sites in the host together with the ET are conducive to weaken the CR process of Tb3+/Sm3+, leading to high PL efficiency. Finally, a prototype pc-wLED assembled via a remote ‘capping’ packaging strategy and by using only the stably composition-optimized white-emitting LYS: Ce3+/Tb3+/Sm3+ demonstrates that the phosphor is promising for high-quality of light.

Neural net analysis of NMR spectra from strongly-coupled spin systems

Extracting parameters such as chemical shifts and coupling constants from proton NMR spectra is often a first step in using spectra for compound identification and structure determination. This can become challenging when scalar couplings between protons are comparable in size to chemical shift differences (strongly coupled), as is often the case with low-field (bench top) spectrometers. Here we explore the potential utility of AI methods, in particular neural networks, for extracting parameters from low-field spectra. Rather than seeking large experimental sets of spectra for training a network, we chose quantum mechanical simulation of sets, something that is possible with modern software packages and computer resources. We show that application of a network trained on 2-D J-resolved spectra and applied to a spectrum of iduronic acid, shows some promise, but also meets with some obstacles. We suggest that these may be overcome with improved pulse sequences and more extensive simulations.

Self-Consistent Determination of Single-Impurity Anderson Model Using Hybrid Quantum-Classical Approach on a Spin Quantum Simulator.

The accurate determination of the electronic structure of strongly correlated materials using first principle methods is of paramount importance in condensed matter physics, computational chemistry, and material science. However, due to the exponential scaling of computational resources, incorporating such materials into classical computation frameworks becomes prohibitively expensive. In 2016, Bauer etal. proposed a hybrid quantum-classical approach to correlated materials [B. Bauer et al., Hybrid quantum-classical approach to correlated materials, Phys. Rev. X 6, 031045 (2016).PRXHAE2160-330810.1103/PhysRevX.6.031045] that can efficiently tackle the electronic structure of complex correlated materials. Here, we experimentally demonstrate that approach to tackle the computational challenges associated with strongly correlated materials. By seamlessly integrating quantum computation into classical computers, we address the most computationally demanding aspect of the calculation, namely the computation of the Green's function, using a spin quantum processor. Furthermore, we realize a self-consistent determination of the single impurity Anderson model through a feedback loop between quantum and classical computations. A quantum phase transition in the Hubbard model from the metallic phase to the Mott insulator is observed as the strength of electron correlation increases. As the number of qubits with high control fidelity continues to grow, our experimental findings pave the way for solving even more complex models, such as strongly correlated crystalline materials or intricate molecules.

Advances and Challenges in Scoring Functions for RNA–Protein Complex Structure Prediction

RNA–protein complexes play a crucial role in cellular functions, providing insights into cellular mechanisms and potential therapeutic targets. However, experimental determination of these complex structures is often time-consuming and resource-intensive, and it rarely yields high-resolution data. Many computational approaches have been developed to predict RNA–protein complex structures in recent years. Despite these advances, achieving accurate and high-resolution predictions remains a formidable challenge, primarily due to the limitations inherent in current RNA–protein scoring functions. These scoring functions are critical tools for evaluating and interpreting RNA–protein interactions. This review comprehensively explores the latest advancements in scoring functions for RNA–protein docking, delving into the fundamental principles underlying various approaches, including coarse-grained knowledge-based, all-atom knowledge-based, and machine-learning-based methods. We critically evaluate the strengths and limitations of existing scoring functions, providing a detailed performance assessment. Considering the significant progress demonstrated by machine learning techniques, we discuss emerging trends and propose future research directions to enhance the accuracy and efficiency of scoring functions in RNA–protein complex prediction. We aim to inspire the development of more sophisticated and reliable computational tools in this rapidly evolving field.

Rapid design method for composite emergency steel piers with thin-walled steel tube framework and discussion on "temporary-permanent" transition

To address the conflict between the reserve of repair materials for existing bridge piers and the demands for emergency repairs, as well as the challenge of converting temporary emergency structures into permanent ones without significant disassembly, a novel composite emergency steel pier has been developed. This pier utilizes commonly available thin-walled steel tube sections as the framework, I-beams as the connecting elements, and incorporates a "temporary-permanent" transition function. Taking the emergency steel pier for medium-height bridge piers in high-speed rail systems as an example, this study introduces three evaluation metrics—security coefficient (n), stability coefficient k), and variation coefficient (V)—analyzing the factors influencing the design and application thresholds of the emergency steel piers from perspectives of strength, stability, and load distribution uniformity. Based on this, a rapid design method for composite emergency steel piers with thin-walled steel tube frameworks that does not require numerical simulation has been developed and experimentally validated. Research findings indicate that when used for the emergency repair of medium-height or lower bridge piers in high-speed railways, the column line stiffness of the thin-walled steel tube framework composite emergency steel piers should range between 0.34 × 10 exp7 kN/mm to 4.15 × 10 exp7 kN/mm. The transverse and longitudinal spacing of the columns should be 1 m to 3 m and 1.5 m to 3 m respectively. The line stiffness of the plinth beams I and II should be greater than 0.69 kN/mm and 1.01 kN/mm respectively. Within these parameter ranges, the emergency steel pier will not experience strength failure or instability, and the load distribution among the columns remains uniformly favorable. In applications to other scenarios, the rapid generation of composite emergency steel piers with thin-walled steel tube frameworks can be achieved by following three steps: parameter selection and structural configuration determination, calculation of the pier-beam linear stiffness ratio, and criterion-based result verification. The rapid design and implementation of composite emergency steel piers help alleviate the contradiction between material stockpiling and repair demands. Furthermore, the pre-designed "temporary-permanent" transition functionality facilitates integrated operations for emergency repairs and permanent restorations.